activity
20242026
collaborators

11 papers

cs.CL2026

Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling

Andrea Brunello, Cristian Curaba, Luca Geatti +3

Accurate translation from Natural Language to First-Order Logic (NL-to-FOL) underpins neurosymbolic AI systems and Natural Language Inference (NLI), making the quality of NL-to-FOL…

cs.AI2026

Synthesis of timeline-based planning strategies avoiding determinization

Dario Della Monica, Angelo Montanari, Pietro Sala

Qualitative timeline-based planning models domains as sets of independent, but interacting, components whose behaviors over time, the timelines, are governed by sets of qualitative…

cs.AI2025

Do LLMs Really Struggle at NL-FOL Translation? Revealing their Strengths via a Novel Benchmarking Strategy

Andrea Brunello, Luca Geatti, Michele Mignani +2

Due to its expressiveness and unambiguous nature, First-Order Logic (FOL) is a powerful formalism for representing concepts expressed in natural language (NL). This is useful, e.g.…

cs.FL2025

Automata-less Monitoring via Trace-Checking (Extended Version)

Andrea Brunello, Luca Geatti, Angelo Montanari +1

In runtime verification, monitoring consists of analyzing the current execution of a system and determining, on the basis of the observed finite trace, whether all its possible con…

cs.AI2025

Interpretable Early Failure Detection via Machine Learning and Trace Checking-based Monitoring

Andrea Brunello, Luca Geatti, Angelo Montanari +1

Monitoring is a runtime verification technique that allows one to check whether an ongoing computation of a system (partial trace) satisfies a given formula. It does not need a com…

cs.LO2025

Complexity of Safety and coSafety Fragments of Linear Temporal Logic

Alessandro Artale, Luca Geatti, Nicola Gigante +2

Linear Temporal Logic (LTL) is the de-facto standard temporal logic for system specification, whose foundational properties have been studied for over five decades. Safety and cosa…